Launching the Data Disasters project
From academic training to real world data analysis
Workflows for querying databases via R
Simple, self-contained, reproducible examples are a common part of good software documentation. However, in the spirit of brevity, these examples often do not demonstrate the most sustainable or flexible workflows for integrating software tools into large projects.
Understanding the data (error) generating processes for data validation
A data consumer’s guide to validating data based on the failure modes data producer’s try to avoid
A Tale of Six States: Flexible data extraction with scraping and browser automation
Exploring how
Playwright's headless browser automation (and its friends) can help unite the states’ data
Embedding column-name contracts in data pipelines with dbt
dbt supercharges SQL with Jinja templating, macros, and testing – all of which can be customized to enforce controlled vocabularies and their implied contracts on a data model
Causal design patterns for data analysts
An informal primer to causal analysis designs and data structures
Resource Round-Up: Causal Inference
Free books, lectures, blogs, papers, and more for a causal inference crash course
Building a team of internal R packages
On the jobs-to-be-done and design principles for internal tools
Generating SQL with {dbplyr} and sqlfluff
Using the tidyverse’s expressive data wrangling vocabulary as a preprocessor for elegant SQL scripts. (Image source techdaily.ca)
Introducing the {convo} package
An R package for maintaining controlled vocabularies to encode contracts between data producers and consumers
